Despite lingering concerns about security, reliability and, yes, costs, the enterprise is still very eager to migrate workloads to the cloud. And not surprisingly, cloud providers are equally eager to take on enterprise workloads.
So what’s the problem? From an operational perspective, the main stumbling block appears to be the lack of effective tools to manage the data environment once it leaves the confines of the data center. And this becomes particularly worrisome when, as is often the case, data is not limited to a single provider but is divided among many.
This is why cloud orchestration continues to be a primary, albeit elusive, goal for the enterprise. According to Persistence Market Research, orchestration is on pace to top $20 billion in market value by 2025, representing 14.6 percent compound annual growth. The main driver will be the increased use of SaaS-based management solutions, which are becoming increasingly embedded in broader cloud management stacks. As the need for more efficient infrastructure grows, these platforms will naturally seek to spread workloads to the lowest-cost provider while still maintaining centralized control for the data owner. And this phenomenon is equally prevalent among small businesses and multinational conglomerates.
- Cloud orchestration, in fact, is becoming such an important element to emerging data infrastructure that software developers are starting to break it out as a key business initiative.
- Orchestration within a Linux ecosystem is helpful, but many organizations would no doubt want to extend that to other operating systems, as well.
- New releases provides enhanced security features like event auditing, device management and file system access control, as well as automated workflow management across distributed, heterogeneous RHEL deployments. In addition, the system supports multiple chip-level architectures like IBM Power and z System and 64-Bit ARM.
“While it is always helpful to find just the right infrastructure to support a key workload, too much variety can lead to inefficiency, cost overruns and lost data.”